📅 2024-09-19 — Session: Developed Computational Linear Algebra Course Structure
🕒 15:30–16:20
🏷️ Labels: Course Design, Linear Algebra, Education, Python, Eigenvalues
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to develop a comprehensive course structure for Computational Linear Algebra, focusing on both theoretical concepts and practical applications.
Key Activities
- Developed an initial framework for the course, emphasizing the introduction of theoretical concepts alongside practical applications.
- Created a detailed curriculum outline covering basic to advanced topics such as LU decomposition, QR decomposition, eigenvalues, eigenvectors, and iterative methods.
- Designed class structures for specific topics like eigenvalues and eigenvectors, including interactive Python exercises.
- Planned a class on PA=LU decomposition and Leontief models, concluding with eigenvalues and eigenvectors.
Achievements
- A structured course curriculum was created, incorporating both theoretical and practical elements.
- Lesson plans were developed for key topics, ensuring a balanced approach to theory and practice.
Pending Tasks
- Further development of interactive components and Python exercises to enhance student engagement.
- Review and refinement of lesson plans to ensure clarity and effectiveness.